In late 2023, Tennis Channel brought in AMC Networks and PBS Digital veteran Matthew Graham to spearhead the development of the network's DTC app. In this Q&A, Graham delves into the app's content, ...

When Season 5 of “The Bear” debuts on June 25, it will mark the first returning FX on Hulu series that will simultaneously ...

With so much focus in the media industry on the changing TV landscape, it goes without saying that understanding audience behavior is critical. But advertisers, agencies and publishers need to know ...

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad ...

The Linear cloudy issue tracker and project manager has introduced an AI agent and plans to add AI coding assistance, with CEO and co-founder Karri Saarinen declaring that "issue tracking is dead." ...

In the evolving landscape of decision intelligence, few mathematical breakthroughs have had as profound an impact as linear programming. At the heart of this revolutionary approach stands a brilliant ...

Quantum computing is a groundbreaking technology that promises to transform the way complex problems are solved. Diving into quantum programming may seem daunting, but a structured approach can ...

Through the lens of overall TV viewing, September looked very similar to August, masking the nuances that illuminate true audience behavior. While total usage was generally flat with August, viewing ...

This research paper was presented at the 28 th ACM SIGPLAN International Conference on Functional Programming (opens in new tab) (ICFP), a premier forum for discussing design, implementations, ...

This library is a generalization of SINDy, to be used for the reconstruction of dynamical systems with strong nonlinearities, which require the introduction of a combinatorial search in the elementary ...

As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven successful in various fields, most recently in deep learning. To apply PWLNN methods, both the representation and ...

Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these ...